Identification and inner relation between gastrointestinal stromal tumor and intra-abdominal desmoid tumor / 中华胃肠外科杂志

Intra-abdominal desmoid tumor (IADT) and gastrointestinal stromal tumor (GIST) are both mesenchymal tumors mostly found in gastrointestinal tracts and easily misdiagnosed, which would directly damage the survival prognosis and quality of life of patients. With the advent of the era of precision medicine, the understanding of the above two diseases is more in-depth, and the requirements for accurate diagnosis and individualized precision treatment are more stringent. Moreover, there seems to be some internal relationship between IADT and GIST, and the lack of systematic research and discussion makes clinical decision-making and patient management easy to fall into traps and misunderstandings. Therefore, this paper reviews the clinical characteristics, pathogenesis and treatments of the two, and explore their differences and internal relations, so as to provide research and practical reference for promoting more precise and individualized diagnosis and treatment regimens.

Clinicopathological features and prognosis of gastrointestinal stromal tumors with KIT/PDGFRA gene "homozygous mutation": a multicenter retrospective cohort study / 中华胃肠外科杂志

Objective: To investigate the clinicopathological features of gastrointestinal stromal tumor (GIST) with KIT/PDGFRA "homozygous mutation", the efficacy of targeted therapy and the prognosis. Methods: A retrospective cohort study and propensity score matching were used. "Homozygous mutation" was defined as the detection of KIT/PDGFRA gene status of GIST by Sanger sequencing, which showed that there was only mutant gene sequence in the sequencing map, lack of wild-type sequence or the peak height of mutant gene sequence was much higher than that of wild-type gene sequence (> 3 times). "Heterozygous mutation" was defined as the mutant gene sequences coexisted with wild type gene sequences, and the peak height was similar (3 times or less). The clinicopathological data and follow-up information of 92 GIST patients with KIT/PDGFRA "homozygous mutation" were collected from 4 hospitals in Shanghai from January 2008 to May 2021 (Renji Hospital, Shanghai Jiaotong University School of Medicine: 70 cases; Zhongshan Hospital, Fudan University: 14 cases; Changhai Hospital, Naval Military Medical University: 6 cases and Ruijin Hospital, Shanghai Jiaotong University School of Medicine: 2 cases). Patients with perioperative death, other malignancies, and incomplete clinicopathological information were excluded. The clinicopathological features of the patients and the efficacy of targeted drug therapy were observed and analyzed. The efficacy was evaluated using Choi criteria, which were divided into complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD). In addition, a total of 230 patients with high-risk GIST with "heterozygous mutation" in exon 11 of KIT gene and 117 patients with recurrent or metastatic GIST with "heterozygous mutation" in exon 11 of KIT gene were included. The propensity score matching method was used to match GIST patients with "heterozygous" and "homozygous" mutations in exon 11 of KIT gene (1∶1) for survival analysis. The disease-free survival (DFS) between two groups of high-risk GIST patients who underwent complete surgical resection were compared. And progression-free survival (PFS) in patients with recurrent or metastatic GIST were compared. Results: Of the 92 GIST cases with KIT/PDGFRA "homozygous mutation", 58 were males and 34 were females, with a median onset age of 62 (31-91) years. Primary GIST 83 cases. Primary high-risk GIST (53 cases), metastatic GIST (21 cases) and recurrent GIST (9 cases) accounted for 90.2% (83/92). There were 90 cases of KIT gene"homozygous mutation" (exon 11 for 88 cases, exon 13 for 1 case, exon 17 for 1 case), and 2 cases of PDGFRA gene "homozygous mutation" (exon 12 for 1 case, exon 18 for 1 case). The median follow-up time was 49 (8-181) months. Among the 61 cases of primary localized GIST undergoing complete surgical resection, 2 cases were intermediate-risk GIST, 5 cases were low-risk GIST, and 1 case was very low-risk GIST, of whom 1 case of intermediate-risk GIST received 1-year adjuvant imatinib mesylate (IM) therapy after operation, and no tumor recurrence developed during the follow-up period. The remaining 53 cases were high-risk GIST, and follow-up data were obtained from 50 cases, of whom 22 developed tumor recurrence during follow-up. Of 9 patients directly receiving neoadjuvant targeted therapy (IM or avapritinib), 5 had complete imaging follow-up data, and the evaluation of efficacy achieved PR. Of all the 92 GIST cases with KIT/PDGFRA "homozygous mutation", 50 (54.4%) had tumor metastasis or tumor recurrence or progression during follow-up, and 12 (13.0%) died of the tumor. Survival analysis combined with propensity score showed that in 100 cases of high-risk GISTs with complete resection, GISTs with "homozygous mutation" in exon 11 of KIT gene had shorter disease-free survival (DFS) than GISTs with "heterozygous mutation" in exon 11 of KIT gene (median DFS: 72 months vs. 148 months, P=0.015). In 60 cases of recurrent or metastatic GISTs with KIT gene exon 11 mutation, IM was used as the first-line treatment, and the progression-free survival (PFS) of GISTs with "homozygous mutation" was shorter compared to GISTs with "heterozygous mutation" (median PFS: 38 months vs. 69 months, P=0.044). The differences were statistically significant. Conclusions: "Homozygous mutation" in KIT/PDGFRA gene is associated with the progression of GIST. The corresponding targeted therapeutic drugs are still effective for GIST with KIT/PDGFRA gene "homozygous mutation". Compared with GIST patients with "heterozygous mutation" in KIT exon 11, GIST patients with "homozygous mutation" in KIT exon 11 are more likely to relapse after surgery and to develop resistance to IM. Therefore, it is still necessary to seek more effective treatment methods for this subset of cases.

Clinical significance of the deep learning algorithm based on contrast-enhanced CT in the differential diagnosis of gastric gastrointestinal stromal tumors with a diameter ≤ 5 cm / 中华胃肠外科杂志

Objective: Contrast-enhanced CT is an important method of preoperative diagnosis and evaluation for the malignant potential of gastric submucosal tumor (SMT). It has a high diagnostic accuracy rate in differentiating gastric gastrointestinal stromal tumor (GIST) with a diameter greater than 5 cm from gastric benign SMT. This study aimed to use deep learning algorithms to establish a diagnosis model (GISTNet) based on contrast-enhanced CT and evaluate its diagnostic value in distinguishing gastric GIST with a diameter ≤ 5 cm and other gastric SMT before surgery. Methods: A diagnostic test study was carried out. Clinicopathological data of 181 patients undergoing resection with postoperative pathological diagnosis of gastric SMT with a diameter ≤ 5 cm at Department of Gastrointestinal Surgery of Renji Hospital from September 2016 to April 2021 were retrospectively collected. After excluding 13 patients without preoperative CT or with poor CT imaging quality, a total of 168 patients were enrolled in this study, of whom, 107 were GIST while 61 were benign SMT (non-GIST), including 27 leiomyomas, 24 schwannomas, 6 heterotopic pancreas and 4 lipomas. Inclusion criteria were as follows: (1) gastric SMT was diagnosed by contrast-enhanced CT before surgery; (2) preoperative gastroscopic examination and biopsy showed no abnormal cells; (3) complete clinical and pathological data. Exclusion criteria were as follows: (1) patients received anti-tumor therapy before surgery; (2) without preoperative CT or with poor CT imaging quality due to any reason; (3) except GIST, other gastric malignant tumors were pathologically diagnosed after surgery. Based on the hold-out method, 148 patients were randomly selected as the training set and 20 patients as the test set of the GISTNet diagnosis model. After the GISTNet model was established, 5 indicators were used for evaluation in the test set, including sensitivity, specificity, positive predictive value, negative predictive value and the area under the receiver operating curve (AUC). Then GISTNet diagnosis model was compared with the GIST-risk scoring model based on traditional CT features. Besides, in order to compare the accuracy of the GISTNet diagnosis model and the imaging doctors in the diagnosis of gastric SMT imaging, 3 radiologists with 3, 9 and 19 years of work experience, respectively, blinded to clinical and pathological information, tested and judged the samples. The accuracy rate between the three doctors and the GISTNet model was compared. Results: The GISTNet model yielded an AUC of 0.900 (95% CI: 0.827-0.973) in the test set. When the threshold value was 0.345, the sensitivity specificity, positive and negative predictive values of the GISTNet diagnosis model was 100%, 67%, 75% and 100%, respectively. The accuracy rate of the GISTNet diagnosis model was better than that of the GIST-risk model and the manual readings from two radiologists with 3 years and 9 years of work experience (83% vs. 75%, 60%, 65%), and was close to the manual reading of the radiologist with 19 years of work experience (83% vs. 80%). Conclusion: The deep learning algorithm based on contrast-enhanced CT has favorable and reliable diagnostic accuracy in distinguishing gastric GIST with a diameter ≤ 5 cm and other gastric SMT before operation.